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Estimating the extinction date of the thylacine with mixed certainty data

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The thylacine (Thylacinus cynocephalus), one of Australia's most characteristic megafauna, was the largest marsupial carnivore until hunting, and potentially disease, drove it to extinction in 1936. Though thylacines were restricted to Tasmania for two millennia prior to their extinction, recent “plausible” sightings on the Cape York Peninsula in northern Queensland have emerged, leading some to speculate the species may persist, undetected. Here we show that the continued survival of the thylacine is entirely implausible based on most current mathematical theories of extinction. We present a dataset including physical evidence, expert-validated sightings, and unconfirmed sightings leading up to the present day, and use a range of extinction models, focusing on a Bayesian approach that incorporates all three types of data by modelling valid and invalid sightings as independent processes, to evaluate the likelihood of the thylacine's persistence. Although the last captive individual died in September 1936, our analyses suggest the most likely extinction date would be 1940; other extinction models estimated the thylacine's extinction date between 1936 and 1943, and even the most optimistic scenario suggests the species did not persist beyond 1956. The search for the thylacine, much like similar efforts to “rediscover” other recently extinct charismatic taxa, is likely to be fruitless, especially given that persistence on Tasmania would have been no guarantee the species could reappear in regions that had been unoccupied for millennia. The search for the thylacine may become a rallying point for conservation and wildlife biology, and could indirectly help fund and support critical research in understudied areas like Cape York. However, our results suggest that attempts to rediscover the thylacine will likely be unsuccessful. This article is protected by copyright. All rights reserved
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Research Note
Estimating the extinction date of the thylacine
with mixed certainty data
Colin J. Carlson ,1Alexander L. Bond,2and Kevin R. Burgio 3
1Department of Environmental Science, Policy, and Management, University of California, Berkeley, 130 Mulford Hall, Berkeley, CA
94720, U.S.A.
2Ardenna Research, Potton, Sandy, Bedfordshire SG19 2QA, U.K.
3Department of Ecology and Evolutionary Biology, University of Connecticut, 75 N. Eagleville Road, U-3043, Storrs, CT 06269, U.S.A.
Abstract: The thylacine (Thylacinus cynocephalus), one of Australia’s most characteristic megafauna, was the
largest marsupial carnivore until hunting, and potentially disease, drove it to extinction in 1936. Although
thylacines were restricted to Tasmania for 2 millennia prior to their extinction, recent so-called plausible
sightings on the Cape York Peninsula in northern Queensland have emerged, leading some to speculate the
species may have persisted undetected. We compiled a data set that included physical evidence, expert-validated
sightings, and unconfirmed sightings up to the present day and implemented a range of extinction models
(focusing on a Bayesian approach that incorporates all 3 types of data by modeling valid and invalid sightings
as independent processes) to evaluate the likelihood of the thylacine’s persistence. Although the last captive
individual died in September 1936, our results suggested that the most likely extinction date would be 1940.
Our other extinction models estimated the thylacine’s extinction date between 1936 and 1943, and the most
optimistic scenario indicated that the species did not persist beyond 1956. The search for the thylacine, much
like similar efforts to rediscover other recently extinct charismatic taxa, is likely to be fruitless, especially given
that persistence on Tasmania would have been no guarantee the species could reappear in regions that had
been unoccupied for millennia. The search for the thylacine may become a rallying point for conservation and
wildlife biology and could indirectly help fund and support critical research in understudied areas such as
Cape York. However, our results suggest that attempts to rediscover the thylacine will be unsuccessful and that
the continued survival of the thylacine is entirely implausible based on most current mathematical theories
of extinction.
Keywords: sighting record, Tasmania, Tasmanian tiger
Estimaci´
on de la Fecha de Extinci´
on del Tilacino con Datos Mixtos de Certidumbre
Resumen: El tilacino (Thylacinus cynocephalus), una de las especies de megafauna m´
as caracter´
ısticas de
Australia, era el carn´
ıvoro marsupial m´
as grande hasta que la caza, y potencialmente las enfermedades, lo
llev´
o a la extinci´
on en 1936. Aunque los tilacinos estuvieron restringidos a Tasmania durante dos milenios
previos a su extinci´
on, recientemente han emergido presuntos avistamientos plausibles en la pen´
ınsula de
Cape York al norte de Queensland, lo que ha llevado a algunos a especular que la especie pudo haber persistido
sin ser detectada. Recopilamos un conjunto de datos que incluy´
o evidencia f´
ısica, avistamientos validados por
expertos, y avistamientos sin confirmaci´
on hasta el d´
ıa de hoy, e implementamos una gama de modelos de
extinci´
on (enfocados en la estrategia bayesiana que incorpora los tres tipos de datos al modelar avistamientos
v´
alidos e inv´
alidos como procesos independientes) para evaluar la probabilidad de la persistencia del tilacino.
Aunque el ´
ultimo individuo cautivo muri´
o en septiembre de 1936, nuestros resultados sugirieron que la
fecha m´
as probable de extinci´
on habr´
ıa sido en 1940. Nuestros otros modelos de extinci´
on estimaron la
fecha de extinci´
on del tilacino entre 1936 y 1943, y el escenario m´
as optimista indic´
o que la especie no
persisti´
om
´
as all´
a de 1956. Es probable que la b´
usqueda del tilacino, como muchos esfuerzos similares para
email cjcarlson@berkeley.edu
Article impact statement: The search for thylacine in Australia is likely to be unsuccessful, and search costs will drain limited conservation
resources.
Paper submitted May 7, 2017; revised manuscript accepted October 11, 2017.
1
Conservation Biology, Volume 00, No. 0, 1–7
C
2017 Society for Conservation Biology
DOI: 10.1111/cobi.13037
2The Extinct Thylacine
redescubrir a otros taxones carism´
aticos recientemente extintos, sea infruct´
ıfera, especialmente debido a que
la persistencia en Tasmania no habr´
ıa sido garant´
ıa de que la especie pudiera reaparecer en regiones que no
hab´
ıan sido ocupadas durante milenios. La b´
usqueda del tilacino podr´
ıa convertirse en un punto de reuni´
on
para la biolog´
ıa de la conservaci´
on y de la vida silvestre y podr´
ıa ayudar indirectamente a financiar y a
apoyar investigaciones cr´
ıticas en ´
areas que no han sido estudiadas suficientemente, como Cape York. Sin
embargo, nuestros resultados sugieren que los intentos por redescubrir al tilacino no ser´
an exitosos y que la
supervivencia continuada del tilacino es completamente implausible con base en las teor´
ıas matem´
aticas de
extinci´
on m´
as recientes.
Palabras Clave: registro de avistamientos, Tasmania, tigre de Tasmania
:

(Thylacinus cynocephalus)

,

1936
,
,

,
(

,

,
)
1936
9
,

1940
19361943
,

1956
,

,
,


,
(
)
,

,

,
:

;
:
:,,
Introduction
The history of conservation biology has included a few
exceptional errors, in which experts have pronounced
a species extinct only for it to be later rediscovered.
Perhaps, most famous are Lazarus taxa known originally
from the fossil record (e.g., the coelacanth [Latimeria
sp.] and dawn redwood [Metasequoia sp.]), but even
recently declared species extinctions can also sometimes
be overturned. Hope of rediscovering a supposedly ex-
tinct species can inspire volumes of peer-reviewed re-
search, and sometimes a single controversial sighting
(e.g., Fitzpatrick et al. 2005) can be enough to reignite
controversy and justify seemingly endless field inves-
tigation, as in the ongoing search for the Ivory-Billed
Woodpecker (Campephilus principalis) despite all odds
(National Audubon Society 2016). Similarly, in Queens-
land, Australia, 2 unconfirmed sightings in early 2017
have inspired a new search for the thylacine (Thylacinus
cynocephalus).
The thylacine, or Tasmanian tiger, has been presumed
extinct since the last captive specimen died on 7 Septem-
ber 1936 (Sleightholme & Campbell 2016). Thylacines are
believed to have gone extinct on the Australian mainland
2 millennia ago, thereafter persisting only as Tasmanian
endemics (Paddle 2002). State-sponsored eradication in
Tasmania between 1886 and 1909 caused a devastat-
ing population crash (Sleightholme & Campbell 2016).
This eradication campaign, combined with prey declines,
could have been sufficient extinction pressure (Prowse
et al. 2013), but other research strongly suggests that a
disease similar to canine distemper could have helped
drive the species to extinction (De Castro & Bolker 2005;
Paddle 2012). Although the mechanism has been a topic
of debate, the extinction status of the thylacine has been
essentially unchallenged in peer-reviewed literature. De-
spite this, sightings have continued throughout Tasma-
nia and mainland Australia, often gathering national and
international media attention. In January 2017, 2 uncon-
firmed “detailed and plausible” sightings in the Cape York
Peninsula in northern Queensland sparked renewed in-
terest in the thylacine’s persistence, particularly in the
Australian mainland. Researchers currently intend to in-
vestigate those sightings with camera traps later this year
(James Cook University 2017).
Is there empirical support for this most recent search?
Extinction-date (τE) estimators have been a key part of
parallel debates about the Ivory-billed Woodpecker. What
little work has been done on the thylacine places τEfrom
1933 to 1935; only 1 model (using temporally subset-
ted data) suggests the species might be extant (Fisher
& Blomberg 2012). A subsequent study suggested that
based on search effort, thylacine’s body size, and former
density, they would have been rediscovered by 1983 if
they were still extant (Lee et al. 2017b). These methods
exclude sightings data, but recently developed Bayesian
models differentiate between the processes of verified
and unverified sightings explicitly, allowing researchers
to include uncertain sightings in models as a separate
class of data (Solow & Beet 2014). We applied those
Conservation Biology
Volume 00, No. 0, 2018
Carlson et al. 3
models (and several other extinction date estimators) to
thylacine sightings and asked: What is the probability that
the species might be rediscovered?
Methods
Most of the sightings in our data set are from Sleightholme
and Campbell’s (2016) appendix (covering 1937–1980),
which includes 1167 post-1900 sightings classified as a
capture, kill, or sighting and Smith et al.’s (1981) sum-
mary of 243 sightings from 1936 to 1980. Additional
sightings were compiled from Heberle (2004), records
on public websites maintained by interested citizen
groups (www.tasmanian-tiger.com, www.thylacineresea
rchunit.org, and www.thylacineawarenessgroup.com),
and online news stories from 2007 to 2016. We scored
records as 1, physical evidence (e.g., from bounty
records, museum specimens, or confirmed captures); 2,
confirmed sighting (sightings agreed as valid by experts);
or 3, unconfirmed sighting (sightings not considered valid
by experts) (Fig. 1). For each year from 1900 to 1939,
we used the sighting of the highest evidentiary qual-
ity; captures or killed individuals were physical evidence
(n=101) (Supporting Information). Our assembled data
set spanned from 1900 to 2016 and included the last
confirmed specimen collected in 1937. Thirty-six of the
years included confirmed sightings. There was only 1
instance of an expert sighting without physical evidence
(1932). The remaining sightings in the data set were
unconfirmed sightings. Although this reduction to 1
record per year was required by only some models, we
aimed for data consistency across methods. Because there
were also likely unreported unconfirmed sightings, we
also ran models based on the assumption that an uncon-
firmed sighting occurred annually from 1938 (the 1st year
with no verified sightings or specimens) to 2016, which
produced a marginally higher chance of persistence but
without changing the overall conclusions (Supporting
Information).
For all analyses, we considered the species across its
historical range (i.e., mainland Australia and Tasmania)
and included valid sightings from Tasmania alongside
highly questionable sightings from mainland Australia,
despite the species’ supposed extirpation 2 millennia
earlier on the continent. We considered this the only op-
timistic modeling scenario for the thylacine’s persistence
in which recent high-profile sightings could be valid,
even if it represents one of the most biologically implau-
sible scenarios. In Supporting Information, we present an
analysis in which we used only confirmed sightings from
Tasmania, which could be considered a more realistic
analysis of the probability that the thylacine persisted on
Tasmania alone (although this would fail to explain the
most controversial recent sightings throughout mainland
Australia) (Supporting Information).
Bayesian Extinction Estimators
Methods to estimate extinction dates from time series
data have been popular in conservation biology since
the 1990s, but the majority fail to account for the vari-
ability in quality and certainty of most sighting records
(Boakes et al. 2015). However, several Bayesian methods
have been developed recently that incorporate variable
sighting quality, including unconfirmed sightings, in es-
timation of extinction date. These methods rely on the
assumption that the probability a species is extinct (an
event E), based on a time series of sightings t=(t1,...,tn),
is expressed by Bayes’ theorem:
P(E|t)=P(t|E)
p(t)P(E)
=P(t|E)P(E)
p(t|E)p(E)+p(t|¯
E)(1 p(E)),(1)
Figure 1. Thylacine sighting
data (confirmed specimens,
absolute and certain form
of evidence; confirmed
sightings, expert-verified
sightings of intermediate
level of certainty;
unconfirmed sightings,
controversial sightings or
indirect evidence based on
scat or tracks, weakest
source of evidence).
Conservation Biology
Volume 00, No. 0, 2018
4The Extinct Thylacine
and where ¯
Eis the scenario that the species is not extinct
within the period in question. The prior probability of
extinction P(E) can often be hard to define, although
it is sometimes uninformatively set to 0.5 for explicit
estimation of P(E|t). However, the Bayes factor can be
used as a test of support for Ewhere
B(t)=p(t|E)
p(t|¯
E)(2)
(although it can be formatted in reverse in some studies,
as in the case of Lee et al. [2014], given the probability
that a species persists). The relationship between the
Bayes factor and the probability of the species’ extinction
is given as
P(E|t)=1
1+1P(E)
P(E)B(t).(3)
Consequently, with an uninformative prior,
P(E|t)=B(t)
B(t)+1,(4)
and given a sufficiently large Bayes factor, the probability
of persistence is
P(¯
E|t)=1
B(t)+11
B(t).(5)
A handful of extinction-date estimation methods have
been developed using Bayesian frameworks that allow es-
timation of the Bayes factor and thereby support hypoth-
esis testing. The set of models on which we focused were
first developed by Solow et al. (2012), who proposed a
method in which all sightings leading up to a date tL(the
date of the last certain sighting) were certain and those
after tLwere uncertain. Valid and invalid sightings were
generated by stationary Poisson processes with different
rates, but certain and uncertain sightings had the same
rate (Solow et al. 2012). A more recent revision (Solow
& Beet 2014) proposes 2 major modifications. In the first
modification (model 1), the same assumptions are made
as in the original method, except that uncertain sight-
ings are permitted before tL.The second modification
(model 2, which we used) differs more notably in that it
also treats certain and uncertain sightings as independent
Poisson processes. This model is recommended for cases
in which certain and uncertain sightings “differ qualita-
tively,” as in our study. For example, we note that blurry
photographic or video evidence and crowdsourced sight-
ing records from citizen groups are unique issues for later,
uncertain thylacine sightings. Therefore, this model is
more appropriate than model 1 (or the model from Solow
and Beet 2012) for our study.
In Solow and Beet’s (2014) model 2, although the rate
of valid sightings is likely to change leading up to an ex-
tinction event, after extinction that rate remains constant
(at zero) and all sightings are presumed unconfirmed. The
sighting data set toccurs over an interval [0,T), where 0
τE<T. During the interval [0, τE), valid sightings occur at
rate , whereas invalid sightings occur at rate , meaning
that valid sightings occur at proportion
=
+.(6)
Confirmed sightings occur, at an independently deter-
mined rate, which divides the data set of sightings tinto
confirmed sightings tcand unconfirmed sightings tu.The
likelihood of the data conditional on τEis given as
p(t|τE)=p(tc|τE)p(tu|τE).(7)
These 2 values are calculated using nc(the number of
confirmed sightings, all before τE)andnu(the number
of unconfirmed sightings), where nu(τE) are the subset
recorded before τE,andωacts as a dummy variable re-
placing :
p(tc|τE)=(nc1)!
(τE)nc
p(tu|τE)=
1
0ωnu(1ω)nunu(τE)τE+1ω
ωTnudω.
(8)
Likelihood p(t|τE) is calculated as the product of those
2terms.
The posterior probability that the species became ex-
tinct in the interval (0,T), which we denoted as an event
E(with alternate hypothesis ¯
E), is given for a prior
p(τE)as
p(t|E)=p(t|τE)p(τE).(9)
The alternate probability p(t|¯
E) can be calculated by
evaluating the same expression given above for p(t|τE)
at τE=T.The Bayes factor is given as
B(t)=p(t|E)
p(t|¯
E),(10)
and expresses the relative support for the hypothesis
that extinction happened in the interval [0,T). The most
subjectivity in the method is therefore introduced in se-
lecting the prior τE. Solow and Beet (2014) suggest 3
possibilities: a linear or exponential decline after the last
confirmed sighting or a uniform (uninformative) prior.
We elected to use the uniform prior in all the models
because it makes the least constrained assumption about
the species’ likely extinction status.
In addition to the models developed by Solow and
Beet (2014), we also included another Bayesian model
(Lee et al. 2014) that builds on similar foundational
work (Solow 1993; Solow et al. 2012). Like Solow and
Beet’s (2014) model 2, the model from Lee et al. (2014)
treats confirmed and unconfirmed sightings as separate
processes, and Lee et al. (2014) make slightly different
recommendations regarding how to select a prior
Conservation Biology
Volume 00, No. 0, 2018
Carlson et al. 5
probability that a given sighting is valid, but the overall
intention of the model is largely the same. The approach
in Lee et al. (2014) is also implemented stochastically
with an Monte Carlo Markov Chain (MCMC) approach in
BUGS, whereas Solow and Beet’s (2014) model calculates
likelihoods explicitly. We implemented the model from
Lee et al. (2014) with some of the simplest possible
assumptions: the false positive rate for confirmed sight-
ings is 0, whereas the false positive rate for unconfirmed
sightings samples from a large uniform distribution.
That method can also be implemented more flexibly by
assigning different priors to different categories of evi-
dence, as Lee et al. (2014) suggest. However, rather than
use somewhat arbitrarily chosen priors to differentiate
among our uncertain reports (a refinement with limited
benefits, per a recent study [Lee et al. 2017a]), we
simply divided our data into confirmed and unconfirmed
sightings. Other Bayesian models existed, but we chose
to include the 2 appropriate recently developed Bayesian
methods with available code (Boakes et al. 2015).
Other Extinction Estimators
For the sake of completeness, we also included several
other widely used non-Bayesian estimators with varying
levels of complexity (Rivadeneira et al. 2009; Boakes et al.
2015) that could be readily calculated with the R package
sExtinct (Clements 2013a). Were we to include every
unconfirmed, controversial sighting up to 2016 and to
treat these as valid sightings (because these models make
no such distinction), all methods would indicate that the
species is unequivocally extant. Consequently, we lim-
ited the implementation of other methods to 2 practical
applications and examined how results changed by either
including only confirmed, uncontroversial specimens or
both confirmed specimens and confirmed sightings (Sup-
porting Information).
Among the methods we included, Robson and Whit-
lock (1964) suggested a nonparametric method based on
the last 2 sightings (with an associated Pvalue):
τE=tn+(tntn1),(11)
p=tntn1
Ttn1
.(12)
This produced the latest thylacine τE(Supporting In-
formation), as expected, given that the method can be
prone to severe overestimation. Burgman et al. (1995)
used the length of the period of observation, the num-
ber of years with and without records, and the length
of the longest consecutive set of years with records to
derive a combinatoric probability of unobserved pres-
ence. Similarly, Strauss and Sadler (1989) developed a
Bayesian method focused on the discrepancy between
the observed interval of sightings (between the first and
last sighting) and the true range of a species in the fossil
record. Setting a precedent on which more current meth-
ods are based, Solow (1993) in his original method as-
sumes that sightings are a stationary Poisson process, in
which the probability of persistence is
p(τE)=tn
τEn
.(13)
However, a subsequent formulation makes the more
accurate assumption that sightings follow a truncated ex-
ponential distribution, declining until extinction (Solow
2005). Finally, the optimal linear estimator (OLE) method
(Roberts & Solow 2003) is the most robust nonparametric
extinction estimator (Clements et al. 2013) and is based
on a subset of the last ssightings of ktotal,
τE=
s
i=1
witki+1;w=b1b11b,(14)
where bis a vector of s1s, and is a square matrix of
dimension swith typical element
ij =(2ˆυ+i)υ+j)
υ+i)(j),(15)
ˆυ=1
s1
s2
i=1
ln tktks+1
tkts+1
.(16)
Results
Based on model 2 from Solow and Beet (2014), the most
likely value for τEwas 1940; the posterior likelihood
declined rapidly thereafter (Fig. 2). The probability the
thylacine is extant was extremely low (Bayes factor =
6.08912 ×1013; equivalently, an odds ratio of 1 in 60.9
trillion). Using Lee et al.’s (2014) method, the probability
of persistence was estimated to be zero by 1940. All of
the non-Bayesian estimating models agreed with these
findings. Using only confirmed specimens provided an
OLE estimated extinction date of 1938 (95% CI 1937–
1943). Adding confirmed sightings did not change the
estimated extinction date or confidence interval. Robson
and Whitlock’s (1964) method gave τEas 1956, the latest
estimate (Table 1 & Supporting Information).
Discussion
Based on the results of our Solow and Beet’s (2014) model
2, it remains plausible that the thylacine’s extinction
could have occurred up to a decade later than believed.
But for thylacines to appear in 2017, especially where
they are believed to have been absent for 2 millennia,
is highly implausible. The 2 sightings from Cape York
described as “detailed” and “plausible” (Hunt 2017) may
Conservation Biology
Volume 00, No. 0, 2018
6The Extinct Thylacine
Figure 2. The posterior probability of
a given thylacine extinction date (τE)
scaled by the area under the entire
likelihood curve. In Solow and Beet’s
(2014) model, specimen-based
records are treated separately and as
certain observations; consequently,
evaluation begins in 1937, the year
of the last certain sighting (i.e.,
extinction prior to that date is not
considered).
Table 1. Main estimates for thylacine extinction dates.
Modela
Explicit inclusion
of uncertainty? τE
Roberts and Solow (2003) no 1938
Solow and Beet (2014)byes 1940
Lee et al. (2014) yes 1940
Strauss and Sadler (1989) no 1940
Solow (1993) no 1941
Solow (2005) no 1942
Burgman et al. (1995) no 1945
Robson and Whitlock (1964) no 1956
aParametric estimates, except the optimal linear estimator, are cal-
culated with a cutoff of α<0.05.
bGiven by the year with the highest posterior likelihood.
cGiven by the posterior probability reaching zero.
be so from a strictly zoological perspective, but from a
modeling standpoint, they fit neatly into a pattern of on-
going, false sightings that follow nearly any high-profile
extinction. However, models can be wrong, and new
data may overturn a century of common knowledge in
what could be one of the most surprising rediscoveries
in conservation history.
The hope of rediscovering extinct species is one of
the most powerful emotional forces in conservation and
can bring attention to threatened species and ecosystems
while igniting public interest (and funding) (Clements
2013b). The search for the thylacine may reap those ben-
efits, and the proposed 2017 search has already gathered
significant attention from journalists and on social me-
dia. Moreover, the data that will be collected during the
search for the thylacine in Cape York may be invaluable
for other conservation studies. But the ongoing search for
extinct species, in the broader sense, likely diverts critical
funds required desperately for the conservation of nearly
extinct species. About 7% of some invertebrate groups
may already have gone extinct, at which rate 98% of all
extinctions would be entirely undetected (R´
egnier et al.
2015). Globally, 36% of mammal species are threatened
with extinction (classified as vulnerable, endangered of
critically endangered by the International Union for Con-
servation of Nature), including 27% of native Australian
mammals (IUCN 2016), and limited resources can be bet-
ter spent reversing those declines than chasing the ghosts
of extinction past.
Acknowledgments
We thank A. Beet for the original Matlab code used in
Solow and Beet (2014), A. Butler (Biomathematics and
Statistics Scotland) for translating the Matlab code into
R, and L. Bartlett for helpful criticism and feedback. We
thank 2 anonymous reviewers for helpful feedback, and
particularly for providing useful code adapting the Open-
Bugs scripts of Lee et al. (2014) for our study.
Supporting Information
The results of supplemental extinction models (Appen-
dices S1–S3) and our data set of thylacine sightings
(Appendix S4) are available online. The authors are solely
responsible for the content and functionality of these
materials. Queries (other than absence of the material)
should be directed to the corresponding author.
Supporting lnformation
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Conservation Biology
Volume 00, No. 0, 2018
... However, hundreds of unverified observations have been reported in Tasmania over subsequent decades. Carlson et al. (2018) used physical evidence and uncertain sightings to analyze the record of thylacine encounters in Tasmania from 1900 to 2015. They concluded that extinction was likely by 1940 and that there was virtually no chance of persistence to the present day (1 in 112 trillion against). ...
... For these unverified sightings, the quality of reports and associated documentation did not noticeably change preto post-1930s (Rounsevell & Smith 1982), except that no more specimens were confirmed. However, there have also been many reports from mainland Australia of quality comparable to those from Tasmania (Lang 2014;Carlson et al. 2018), which argues for a down weighting in the reliability of eyewitness reports alone. Although technological advances (e.g., automated thermal imaging cameras) have improved the likelihood of detection, they are still not distributed widely across the thylacine's plausible relictual geographic range, and these recent innovations say nothing about the possibility of persistence over the few decades following the last verified physical evidence. ...
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... In "Estimating the Extinction Date of the Thylacine with Mixed Certainty Data," we (Carlson et al. 2018a) used the sighting record, including controversial post-1936 sightings, to model the probability that the thylacine has been classified accurately as extinct. We found astronomically low odds that the thylacine is extant and argue that a camera-trap search for the species in Cape York, northern Queensland, may be motivated by false hope. ...
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1.Accurate measures of extinction are needed in biodiversity monitoring and conservation management but ascertaining the exact time at which a species became extinct is difficult since a small population may go undetected for many years.2.For little-studied species, often the only information available is historical sighting data. Several statistical tests have been developed which use this information to make inferences about a species’ extinction. The increasing array of methods can present a daunting choice.3.We review the more frequently cited methods, for each model explaining its assumptions, the data required, the scenarios it was developed for and power considerations, if known. We provide guidance on selecting the most appropriate method for a particular sighting record.4.We give examples from the literature to show how the methods have been usefully applied across conservation research, informing conservation decision-making and extinction inference.This article is protected by copyright. All rights reserved.
Article
While anecdotal accounts exist in the literature of epidemic disease as a significant factor in recent mammalian extinctions, harder data has not previously been presented. The statistics from the deliberate killing of thylacines as a pest species support contemporary records at the turn of the twentieth century, of an epidemic disease in thylacines and other marsupi-carnivores. For the first time, detailed symptoms and statistics of the disease are presented, as recorded by museum staff, and zoological-garden curators and veterinarians. It is argued that the effects of the disease in captivity, which more than halved thylacine longevity, and preferentially affected juveniles, are conformable with the expression of the disease recorded amongst wild thylacines, and demand a recognition of the importance of this disease as a major factor in the thylacine's recent extinction, and its consideration as an influential factor on the distribution and population dynamics of extant marsupi-carnivores. It also practically demonstrates the obvious potential for disease to have been involved in megafaunal extinctions in the past.